The central theme of our P20 award (MH57180), submitted from the University of Minnesota, is modeling and visualization of spatial and temporal patterns of functional activation in the living human brain. The application incorporates two neuroinformatics components, Project 2 (Consensus Patterns in Functional Neuroimaging) and Project 3 (Computational Anatomy and Visualization), both of which involve image registration. Although numerous feature-based 3D registration algorithms (warps) for inter- and intrasubject registration of PET, MRI and fMRI brain volumes have been proposed, the performance of these algorithms has not been optimized with regard to feature hierarchy and selection. Moreover, "goodness-of-warp" criteria may vary depending upon the research question being addressed and the type and quality of MRI/fMRI data. Since the MRI/fMRI research being conducted in Projects 2 and 3 requires high-quality image registration, we propose to systematically evaluate and compare the performance of several automated feature-based registration algorithms. To this end, we will (i) develop a data base of 20 expertly-segmented high-resolution multimodal (T1, T2 and PD) whole-brain MR volumes for the evaluation of intersubject brain image registration, (ii) systematically evaluate the accuracy of automated algorithms for intersubject brain image registration, (iii) create a software framework that allows developers of automatic registration algorithms and users of interactive registration algorithms to systematically explore the utility of using different feature maps for an algorithm's internal computation of image/brain similarity, and (iv) post our labeled brain volumes, software modules and test results on the INC Web site as downloadable distribution sets, together with documentation and log files. This work will be accomplished in collaboration with investigators at McGill University and the University of Pennsylvania. [unreadable] [unreadable]